Patterns of sequence variation within the <i>Neisseria meningitidis</i> lactoferrin binding proteins<sup>1</sup>This article is part of a Special Issue entitled Lactoferrin and has undergone the Journal’s usual peer review process.
Bibliographic record
Abstract
Lactoferrin binding proteins A and B (LbpA and LbpB) compose the lactoferrin receptor of the obligate human pathogen Neisseria meningitidis . This receptor is thought to be important for colonization and initiation of invasive disease because of its role in acquiring host iron and providing protection from the cationic peptide, lactoferricin. By virtue of its function, the receptor is accessible to the host immune system and displays substantial sequence variation. In this study, we analyzed a broad collection of LbpAs (62) and LbpBs (101) to determine the distribution of sequence variation within each protein and to search for patterns between sequence similarity and strain typing. The sequence variation in LbpA was predominantly observed in 3 surface loops and, surprisingly, in the N-terminal region immediately upstream of the predicted TonB box. The analysis of LbpB revealed that the variability was distributed throughout the protein, particularly in the highly variable negatively charged regions in the C-lobe, but otherwise was greater in the N-lobe than the C-lobe. There was no readily identifiable correlation between the sequence variation within LbpA, LbpB, multi-locus sequence type, or serogroup.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".